Git LFS Support: Integrates with Git LFS to manage large resource files effectively, preventing repository bloat. Extensible Backend Support: Aims to support additional Git services like GitLab in future releases. Technical Integration: The extension operates by adding plugins to CKAN (gitdatahubpackage and gitdatahubresource). These plugins hook into CKAN's workflow to automatically write dataset and resource metadata to the configured Git repository. The extension requires configuration via CKAN's .ini file to enable the plugins and provide necessary settings, such as the GitHub API access token. Benefits & Impact: Utilizing the gitdatahub extension provides version control for CKAN metadata, enabling administrators to track changes to datasets and resources over time. The storage of metadata in the Frictionless Data format promotes interoperability and data portability, due to well-defined open standards. Use of Git provides an audit trail and allows others to collaborate and contribute. The extension is helpful when organizations need to keep copy of the metadata outside of CKAN and want to provide an audit trail for their data.

This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms.

The data was extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This supplementary material table was deposited to Zenodo and is identified by the following doi: https://doi.org/10.5281/zenodo.2598799

This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.

It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.

This dataset corresponds to the RDF Linked Data representation of the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms. Most of the semantics resources belong to the OBO foundry.

The transformation to RDF was performed on a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holding the data extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This supplementary material table was deposited to Zenodo and is identified by the following doi: https://doi.org/10.5281/zenodo.2598799

This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.

It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.

This dataset is to be used for the Frictionless Data package testing

NOTE! The data has been removed from this metadata and is nowadays available via FTIA's service for data downloads: https://ava.vaylapilvi.fi/ava/Tie/Tieliikenneonnettomuudet

Finnish Transport Infrastructure Agency collects annual road trafic accident data, which are based on information received from the law enforcement officials, and completes this data with the assistance of Statistics Finland.

This material has been created with Datapackage-standard in mind. For more information, visit: http://frictionlessdata.io/data-packages/

This shared material consists of two tables in CSV-format, and includes information of the accident and involved parties in the accident.

This data does not include any records of traffic accidents that occured in Åland. The X and Y columns are in the standard Finnish ETRS-TM35FIN –format.

A road traffic accident is an accident where there is damage to property and / or personal injury caused by the movement of the vehicle due to a traffic incident. Accident involves at least one moving vehicle , or means of transportation , and has occured in a public road or known road intended for general traffic.

MICA - Muskrat and coypu camera trap observations in Belgium, the Netherlands and Germany is a camera trap observations dataset published by the Research Institute of Nature and Forest (INBO). It is part of the LIFE project MICA, in which innovative techniques are tested for a more efficient control of muskrat and coypu populations, both invasive species. The dataset contains camera trap observations of muskrat and coypu, as well as many other observed species.

Data in this package are exported from the camera trap management system Agouti (https://agouti.eu) and formatted as a Camera Trap Data Package (Camtrap DP).

Files

Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/record/5590881/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• deployments.csv: camera trap deployments. Includes deploymentID, start, end, location and camera setup information.
• media.csv: media files (images/videos) captured by the camera traps. Associated with deployments (deploymentID) and organized in sequences (sequenceID). Includes timestamp and file path.
• observations.csv: observations based on the media files. Associated with deployments (deploymentID) and sequences (sequenceID). Observations can mark non-animal events (camera setup, human, blank) or one or more animal observations (observationType = animal) of a certain taxon, count, age, sex, behaviour and/or individual.

This is test dataset

This archive includes the data behind the Department of Energy's (DOE) Low Income Energy Affordability Data (LEAD) tool. The LEAD tool is an online, interactive platform that helps users make data-driven decisions on energy goals and program planning by improving their understanding of low-income and moderate-income household energy characteristics. The LEAD Tool offers the ability to select and combine geographic areas (state, county, city and census tract) into one customized group so users can see the total area for their customized geographies (e.g., specific service territories). Archived from https://www.energy.gov/scep/low-income-energy-affordability-data-lead-tool

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

Progression of the students in the different exercises of the biological data science courses at the University of Mons, Belgium for the academic year 2019-2020.

Activity of the students was recorded to monitor their individual progression in asynchronous exercises. The courses were taught in flipped classroom by Philippe Grosjean (philippe.grosjean@umons.ac.be) and Guyliann Engels (guyliann.engels@umons.ac.be) the University of Mons. These authors designed almost all the teaching material, the exercises, and the related software. The courses were also taught at the Campus Charleroi by Raphaël Conotte (raphael.conotte@umons.ac.be) that also contributed to a part of the learnr exercises and of the inline course.

How to use these data?

The README file provides detailed information on the purpose, collection and management of the data. The data are presented in tabular format in CSV files. Metadata in the `datapackage.json` document the different tables and their fields. It is in the Frictionless data format (https://frictionlessdata.io). You can get a view of a part of these metadata by uploading the file `datapackage.json` into the inline data package creator at https://create.frictionlessdata.io. There is a large set of libraries and tools for different programming languages available at https://frictionlessdata.io/tooling/libraries/. Otherwise, any CSV library should import the data in your favourite software. Please, note that encoding is UTF8. For R, the {learnitdown} package provides specific functions to import these data and/or convert them in a SQLite database (https://www.sciviews.org/learnitdown/).

For any question, send an email at sdd@sciviews.org.

HUOM! Aineistot on poistettu tältä metatiedolta ja ovat ladattavissa jatkossa Väyläviraston Aineistonvälitysalustalta täältä: https://ava.vaylapilvi.fi/ava/Tie/Tieliikenneonnettomuudet

Väylävirasto kerää vuosittain tieliikenneonnettomuuksiin liittyvää dataa poliisilta saatujen tietojen perusteella ja täydentää ne tilastokeskuksen avustuksella.

Ainesto on toteutettu Datapackage-standardin ohjeiden mukaan. Lisätietoja: http://frictionlessdata.io/data-packages/

Jaettava aineisto sisältää kaksi taulua CSV-muodossa, sisältäen tietoja onnettomuudesta ja sen osallisista. Aineistossa olevat sijaintitiedot (X- ja Y-sarakkeet) ovat ETRS-TM35FIN -koordinaatistossa.

Aineisto ei sisällä tietoja Ahvenanmaalla sattuneista onnettomuuksista.

Tieliikenneonnettomuus on omaisuusvahinkoja ja/tai henkilövahinkoja aiheuttanut kulkuneuvon liikkumisesta johtunut liikennetapahtuma, jossa on ollut osallisena ainakin yksi liikkuva ajo- taikka kulkuneuvo ja joka on tapahtunut liikenteeseen yleisesti käytetyllä alueella.

BOP_RODENT - Rodent specialized birds of prey (Circus, Asio, Buteo) in Flanders (Belgium) is a bird tracking dataset published by the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (http://lifewatch.be/en/gps-tracking-network-large-birds) for the project/study BOP_RODENT, using trackers developed by Ornitela (https://www.ornitela.com). The study has been operational since 2020. In total 18 individuals of 5 bird of prey species have been tagged at several locations in Flanders (Belgium), mainly to study their habitat use and migration behaviour. Data are automatically synced with Movebank and from there periodically archived on Zenodo (see https://github.com/inbo/bird-tracking).

Files

Data in this package are exported from Movebank study 1278021460. Fields in the data follow the Movebank Attribute Dictionary and are described in datapackage.json. Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/records/6580008/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• BOP_RODENT-reference-data.csv: reference data about the animals, tags and deployments.
• BOP_RODENT-gps-yyyy.csv.gz: GPS data recorded by the tags, grouped by year.

Acknowledgements

This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch. Additional funding was provided by Agentschap voor Natuur en Bos (ANB).

Dados Abertos sobre os processos de compras de materiais e serviços realizados pelo Estado e os contratos firmados entre o Estado e terceiros. Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Compras e Contratos do Portal da Transparência do Estado de Minas Gerais. Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas): - ft_compras - ft_compras_contrato - fl_compras_empenho ## Como participar Saiba como contribuir com a documentação deste conjunto de dados! A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição: - Issues: Para iniciar uma discussão sobre melhorias na documentação. - Pull requests: Para sugerir uma alteração concreta na documentação. Todas as contribuições são bem vindas. Alguns exemplos são: * Indicação de expressões imprecisas presentes na documentação; * Sugestões para inclusão de descrições em campos específicos; * Sugestões para clareza na organização das ideias; * Correção de erros de ortografia e gramática. Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual: - Fale Conosco: Dúvidas - Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões. - Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis. - Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações Documentação das principais alterações sofridas por este conjunto de dados. ### [0.1.0] - 2021-12-29 - Versão inicial

Progression of the students in the different exercises of the biological data science courses at the University of Mons, Belgium for the academic year 2020-2021.

Activity of the students was recorded to monitor their individual progression in asynchronous exercises. The courses were taught in flipped classroom by Philippe Grosjean (philippe.grosjean@umons.ac.be) and Guyliann Engels (guyliann.engels@umons.ac.be) the University of Mons. These authors designed almost all the teaching material, the exercises, and the related software. The courses were also taught at the Campus Charleroi by Raphaël Conotte (raphael.conotte@umons.ac.be) that also contributed to a part of the learnr exercises and of the inline course.

How to use these data?

The README file provides detailed information on the purpose, collection and management of the data. The data are presented in tabular format in CSV files. Metadata in the `datapackage.json` document the different tables and their fields. It is in the Frictionless data format (https://frictionlessdata.io). You can get a view of a part of these metadata by uploading the file `datapackage.json` into the inline data package creator at https://create.frictionlessdata.io. There is a large set of libraries and tools for different programming languages available at https://frictionlessdata.io/tooling/libraries/. Otherwise, any CSV library should import the data in your favourite software. Please, note that encoding is UTF8. For R, the {learnitdown} package provides specific functions to import these data and/or convert them in a SQLite database (https://www.sciviews.org/learnitdown/).

For any question, send an email at sdd@sciviews.org.

Tässä tietokokonaisuudessa on luettelo Luxemburgin julkisen sektorin toimittamista rekistereistä. Tiedot on indeksoitu codegouvfr-fetch-data. Tietorakenne on kuvattu tämän mallin kohdassa taulukko Schema-tiedosto.

Jos haluat osallistua tähän datajoukkoon, voit vapaasti osallistua seuraavaan Github-hankkeeseen ongelmien tai vetopyyntöjen kautta: Julkisen sektorin antama avoimen lähdekoodin ohjelmisto Luxemburgissa, luettelo organisaation tileistä

Current version: v1.1

Trove users can create collections of resources using Trove's 'lists'. Metadata describing public lists is available via the Trove API. This dataset was created by harvesting this metadata. To reduce file size, the details of the resources collected by each list are not included, just the total number of resources.

The data was extracted from the Trove API using this notebook from the Trove lists and tags section of the GLAM Workbench.

The data is available as a CSV file entitled trove-lists.csv and contains the following fields:

• created – date the list was created
• id – Trove's unique list identifier
• number_items – number of resources in list
• title – the title of this list
• updated – date the list was last updated

This repository is part of the GLAM Workbench.
If you think this project is worthwhile, you might like to sponsor me on GitHub.

Dados Abertos sobre despesas com diárias de viagens empenhadas, liquidadas e pagas aos servidores públicos pelo Estado. Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Diárias do Portal da Transparência do Estado de Minas Gerais. Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas): - ft_diarias_ ## Como participar Saiba como contribuir com a documentação deste conjunto de dados! A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição: - Issues: Para iniciar uma discussão sobre melhorias na documentação. - Pull requests: Para sugerir uma alteração concreta na documentação. Todas as contribuições são bem vindas. Alguns exemplos são: * Indicação de expressões imprecisas presentes na documentação; * Sugestões para inclusão de descrições em campos específicos; * Sugestões para clareza na organização das ideias; * Correção de erros de ortografia e gramática. Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual: - Fale Conosco: Dúvidas - Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões. - Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis. - Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações Documentação das principais alterações sofridas por este conjunto de dados. ### [0.1.0] - 2021-12-29 - Versão inicial

The EIA Form 191, also known as the Monthly Underground Natural Gas Storage Report, describes the working and base gas in reservoirs, injections, withdrawals, and location of reservoirs by field monthly. Archived from https://www.eia.gov/naturalgas/ngqs/

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

Dados Abertos sobre Planejamento e Monitoramento.

Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Planejamento e Monitoramento do Portal da Transparência do Estado de Minas Gerais.

Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas):

• ft_plan_acao_ppag
• fl_plan_indicador
• ft_plan_indic_referencia
• ft_plan_indic_plan_exec
• fl_plan_programa
• fl_plan_responsavel
• ft_plan_exec_of_tipoorc
• ft_plan_exec_of_territorio
• ft_plan_exec_of_fonte
• fl_plan_acao
• ft_plan_fonte_fin_acao
• ft_plan_prog_fftd
• ft_plan_prog_mensal
• ft_plan_prog_territorial
• ft_plan_execucao_acao
• ft_plan_prog_of_tipoorc
• ft_plan_prog_of_territorio
• ft_plan_prog_of_fonte

Como participar

Saiba como contribuir com a documentação deste conjunto de dados!

A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição:

• Issues: Para iniciar uma discussão sobre melhorias na documentação.
• Pull requests: Para sugerir uma alteração concreta na documentação.

Todas as contribuições são bem vindas. Alguns exemplos são:

• Indicação de expressões imprecisas presentes na documentação;
• Sugestões para inclusão de descrições em campos específicos;
• Sugestões para clareza na organização das ideias;
• Correção de erros de ortografia e gramática.

Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual:

• Fale Conosco: Dúvidas
• Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões.
• Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis.
• Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações

Documentação das principais alterações sofridas por este conjunto de dados.

[0.1.0] - 2022-06-24

• Versão inicial

The United States Wind Turbine Database (USWTDB) provides the locations of land-based and offshore wind turbines in the United States, corresponding wind project information, and turbine technical specifications. Wind turbine records are collected and compiled from various public and private sources, digitized and position-verified from aerial imagery, and quality checked. The USWTDB is available for download in a variety of tabular and geospatial file formats, to meet a range of user/software needs. Dynamic web services are available for users that wish to access the USWTDB as a Representational State Transfer Services (RESTful) web service. Archived from https://energy.usgs.gov/uswtdb/

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

Dados Abertos sobre despesas empenhadas, liquidadas e pagas pelo Estado ano a ano.

Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Despesa do Portal da Transparência do Estado de Minas Gerais.

Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas):

• ft_despesa_<ano>
• fl_despesa_pgto

Como participar

Saiba como contribuir com a documentação deste conjunto de dados!

A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição:

• Issues: Para iniciar uma discussão sobre melhorias na documentação.
• Pull requests: Para sugerir uma alteração concreta na documentação.

Todas as contribuições são bem vindas. Alguns exemplos são:

• Indicação de expressões imprecisas presentes na documentação;
• Sugestões para inclusão de descrições em campos específicos;
• Sugestões para clareza na organização das ideias;
• Correção de erros de ortografia e gramática.

Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual:

• Fale Conosco: Dúvidas
• Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões.
• Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis.
• Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações

Documentação das principais alterações sofridas por este conjunto de dados.

[0.1.0] - 2021-12-29

• Versão inicial